Systems and methods for electric vehicle power flow management

ABSTRACT

A system and methods that enables power flow management at the local level. A power flow manager can coordinate the charging activities of electrical devices, such as electric vehicles. Power flow decisions may based on the site-level information. In addition, power flow management strategies may be optimized. An optimizer can choose a power flow management strategy and electrical devices for implementing a strategy. In the event of a system failure, power spikes may be avoided by using safe failure modes to provide that the charging activities be coordinated in a predictable and non-disruptive manner. The cost of providing power may be reduced using generation stacks of power production. As such, the total daily cost of providing energy generation may be minimized.

This non-provisional patent application claims priority to, and incorporates herein by reference, U.S. Provisional Patent Application No. 61/165,344 filed on Mar. 31, 2009. This application also incorporates herein by reference the following: U.S. patent application Ser. No. 12/252,657 filed Oct. 16, 2008; U.S. patent application Ser. No. 12/252,209 filed Oct. 15, 2008; U.S. patent application Ser. No. 12/252,803 filed Oct. 16, 2008; and U.S. patent application Ser. No. 12/252,950 filed Oct. 16, 2008.

This application includes material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent disclosure, as it appears in the Patent and Trademark Office files or records, but otherwise reserves all copyright rights whatsoever.

FIELD OF THE INVENTION

The present invention relates in general to the field of electric vehicles, and in particular to novel systems and methods for power flow management for electric vehicles.

BACKGROUND OF THE INVENTION

The electric power grid has become increasingly unreliable and antiquated, as evidenced by frequent large-scale power outages. Grid instability wastes energy, both directly and indirectly, e.g. by encouraging power consumers to install inefficient forms of backup generation. While clean forms of energy generation, such as wind and solar, can help to address the above problems, they suffer from intermittency. Hence, grid operators are reluctant to rely heavily on these sources, making it difficult to move away from carbon-intensive forms of electricity.

With respect to the electric power grid, electric power delivered during periods of peak demand costs substantially more than off-peak power. The electric power grid contains limited inherent facility for storing electrical energy. Electricity must be generated constantly to meet uncertain demand, which often results in over-generation (and hence wasted energy) and sometimes results in under-generation (and hence power failures). Distributed electric resources, en masse can, in principle, provide a significant resource for addressing the above problems. However, current power services infrastructure lacks provisioning and flexibility that are required for aggregating a large number of small-scale resources, such as electric vehicle batteries, to meet large-scale needs of power services.

Modern Electric vehicles could benefit in a variety of ways from a centrally controlled smart charging program, wherein a central server coordinates the charging activities of a number of vehicles. Significant opportunities for improvement exist in managing power flow at local level. More economical, reliable electrical power needs to be provided at times of peak demand. Power services, such as regulation and spinning reserves, can be provided to electricity markets to provide a significant economic opportunity. Technologies can be enabled to provide broader use of intermittent power sources, such as wind and solar. What is needed are power flow management systems and methods that manage power flow at the site-level, that implement various power flow strategies for the optimizing how to dispatch the resources under management, that avoid power spikes, and that minimize the total daily cost of providing energy generation.

SUMMARY OF THE INVENTION

In an embodiment, a method for managing power flow at a local site includes site-level charging of electrical devices by a power flow manager. The power flow manager runs a smart charging program, and coordinates charging activities of the electrical devices. The electrical devices may be located at the local site. The method includes receiving site-level information, which is received by the power flow manager. In addition, power flow decisions are made, by the power flow manager, based on the site-level information. Further, power flow to the electrical devices is managed by the power flow manager, wherein the power flow manager responds to requests.

In another embodiment, a method for managing power flow by optimizing multiple power flow management strategies includes coordinating charging activities of electrical devices. The charge activities are coordinated by a power flow manager. Power flow services are also controlled by the power flow manager. A power flow management strategy is chosen by a meta-optimizer, which also chooses the electrical devices to utilize for implementing the power flow management strategy. The power flow management strategies are implemented by the power flow manager.

In one embodiment, a method for managing power flow using safe failure modes includes coordinating charging activities of electrical devices by a power flow manager. The method includes detecting a system failure event by a power flow manager, and implementing a safe failure mode. The safe failure mode implemented by the power flow manager provides that the charging activities be coordinated in a predictable and non-disruptive manner.

In another embodiment, a method for managing power flow uses generation stacks of power production to reduce cost of providing power to electrical devices. This method also includes coordinating charging activities of electrical devices by a power flow manager. In addition, the power flow manager controls a power production stack, which orders available power. A dispatchable load is listed in the power production stack. The dispatchable load is removed based on a cost reduction strategy.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features, and advantages of the invention will be apparent from the following more particular description of embodiments as illustrated in the accompanying drawings, in which reference characters refer to the same parts throughout the various views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating principles of the invention.

FIG. 1 is a diagram of an example of a power aggregation system.

FIGS. 2A-2B are diagrams of an example of connections between an electric vehicle, the power grid, and the Internet.

FIG. 3 is a block diagram of an example of connections between an electric resource and a flow control server of the power aggregation system.

FIG. 4 is a diagram of an example of a layout of the power aggregation system.

FIG. 5 is a diagram of an example of control areas in the power aggregation system.

FIG. 6 is a diagram of multiple flow control centers in the power aggregation system and a directory server for determining a flow control center.

FIG. 7 is a block diagram of an example of flow control server.

FIG. 8A is a block diagram of an example of remote intelligent power flow module.

FIG. 8B is a block diagram of an example of transceiver and charging component combination.

FIG. 8C is an illustration of an example of simple user interface for facilitating user controlled charging.

FIG. 9 is a diagram of an example of resource communication protocol.

FIG. 10 is a diagram of an example of a site power flow manager.

FIG. 11 is a flow chart of an example of a site power flow manager.

FIG. 12 is a flow chart of an example of optimization across multiple power flow management strategies.

FIG. 13 is a flow chart of an example of avoiding power spikes during energy management failures using safe failure modes.

FIG. 14 is a flow chart of an example of generation-stack-aware dispatch of resources.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Reference will now be made in detail to the embodiments of the present invention, examples of which are illustrated in the accompanying drawings.

Overview

Described herein is a power aggregation system for distributed electric resources, and associated methods. In one implementation, a system communicates over the Internet and/or some other public or private networks with numerous individual electric resources connected to a power grid (hereinafter, “grid”). By communicating, the system can dynamically aggregate these electric resources to provide power services to grid operators (e.g. utilities, Independent System Operators (ISO), etc).

“Power services” as used herein, refers to energy delivery as well as other ancillary services including demand response, regulation, spinning reserves, non-spinning reserves, energy imbalance, reactive power, and similar products.

“Aggregation” as used herein refers to the ability to control power flows into and out of a set of spatially distributed electric resources with the purpose of providing a power service of larger magnitude.

“Charge Control Management” as used herein refers to enabling or performing the starting, stopping, or level-setting of a flow of power between a power grid and an electric resource.

“Power grid operator” as used herein, refers to the entity that is responsible for maintaining the operation and stability of the power grid within or across an electric control area. The power grid operator may constitute some combination of manual/human action/intervention and automated processes controlling generation signals in response to system sensors. A “control area operator” is one example of a power grid operator.

“Control area” as used herein, refers to a contained portion of the electrical grid with defined input and output ports. The net flow of power into this area must equal (within some error tolerance) the sum of the power consumption within the area and power outflow from the area.

“Power grid” as used herein means a power distribution system/network that connects producers of power with consumers of power. The network may include generators, transformers, interconnects, switching stations, and safety equipment as part of either/both the transmission system (i.e., bulk power) or the distribution system (i.e. retail power). The power aggregation system is vertically scalable for use within a neighborhood, a city, a sector, a control area, or (for example) one of the eight large-scale Interconnects in the North American Electric Reliability Council (NERC). Moreover, the system is horizontally scalable for use in providing power services to multiple grid areas simultaneously.

“Grid conditions” as used herein, refers to the need for more or less power flowing in or out of a section of the electric power grid, in response to one of a number of conditions, for example supply changes, demand changes, contingencies and failures, ramping events, etc. These grid conditions typically manifest themselves as power quality events such as under- or over-voltage events or under- or over-frequency events.

“Power quality events” as used herein typically refers to manifestations of power grid instability including voltage deviations and frequency deviations; additionally, power quality events as used herein also includes other disturbances in the quality of the power delivered by the power grid such as sub-cycle voltage spikes and harmonics.

“Electric resource” as used herein typically refers to electrical entities that can be commanded to do some or all of these three things: take power (act as load), provide power (act as power generation or source), and store energy. Examples may include battery/charger/inverter systems for electric or hybrid-electric vehicles, repositories of used-but-serviceable electric vehicle batteries, fixed energy storage, fuel cell generators, emergency generators, controllable loads, etc.

“Electric vehicle” is used broadly herein to refer to pure electric and hybrid electric vehicles, such as plug-in hybrid electric vehicles (PHEVs), especially vehicles that have significant storage battery capacity and that connect to the power grid for recharging the battery. More specifically, electric vehicle means a vehicle that gets some or all of its energy for motion and other purposes from the power grid. Moreover, an electric vehicle has an energy storage system, which may consist of batteries, capacitors, etc., or some combination thereof. An electric vehicle may or may not have the capability to provide power back to the electric grid.

Electric vehicle “energy storage systems” (batteries, super capacitors, and/or other energy storage devices) are used herein as a representative example of electric resources intermittently or permanently connected to the grid that can have dynamic input and output of power. Such batteries can function as a power source or a power load. A collection of aggregated electric vehicle batteries can become a statistically stable resource across numerous batteries, despite recognizable tidal connection trends (e.g., an increase in the total number of vehicles connected to the grid at night; a downswing in the collective number of connected batteries as the morning commute begins, etc.) Across vast numbers of electric vehicle batteries, connection trends are predictable and such batteries become a stable and reliable resource to call upon, should the grid or a part of the grid (such as a person's home in a blackout) experience a need for increased or decreased power. Data collection and storage also enable the power aggregation system to predict connection behavior on a per-user basis.

An Example of the Presently Disclosed System

FIG. 1 shows a power aggregation system 100. A flow control center 102 is communicatively coupled with a network, such as a public/private mix that includes the Internet 104, and includes one or more servers 106 providing a centralized power aggregation service. “Internet” 104 will be used herein as representative of many different types of communicative networks and network mixtures (e.g., one or more wide area networks—public or private—and/or one or more local area networks). Via a network, such as the Internet 104, the flow control center 102 maintains communication 108 with operators of power grid(s), and communication 110 with remote resources, i.e., communication with peripheral electric resources 112 (“end” or “terminal” nodes/devices of a power network) that are connected to the power grid 114. In one implementation, power line communicators (PLCs), such as those that include or consist of Ethernet-over-power line bridges 120 are implemented at connection locations so that the “last mile” (in this case, last feet—e.g., in a residence 124) of Internet communication with remote resources is implemented over the same wire that connects each electric resource 112 to the power grid 114. Thus, each physical location of each electric resource 112 may be associated with a corresponding Ethernet-over-power line bridge 120 (hereinafter, “bridge”) at or near the same location as the electric resource 112. Each bridge 120 is typically connected to an Internet access point of a location owner, as will be described in greater detail below. The communication medium from flow control center 102 to the connection location, such as residence 124, can take many forms, such as cable modem, DSL, satellite, fiber, WiMax, etc. In a variation, electric resources 112 may connect with the Internet by a different medium than the same power wire that connects them to the power grid 114. For example, a given electric resource 112 may have its own wireless capability to connect directly with the Internet 104 or an Internet access point and thereby with the flow control center 102.

Electric resources 112 of the power aggregation system 100 may include the batteries of electric vehicles connected to the power grid 114 at residences 124, parking lots 126 etc.; batteries in a repository 128, fuel cell generators, private dams, conventional power plants, and other resources that produce electricity and/or store electricity physically or electrically.

In one implementation, each participating electric resource 112 or group of local resources has a corresponding remote intelligent power flow (IPF) module 134 (hereinafter, “remote IPF module” 134). The centralized flow control center 102 administers the power aggregation system 100 by communicating with the remote IPF modules 134 distributed peripherally among the electric resources 112. The remote IPF modules 134 perform several different functions, including, but not limited to, providing the flow control center 102 with the statuses of remote resources; controlling the amount, direction, and timing of power being transferred into or out of a remote electric resource 112; providing metering of power being transferred into or out of a remote electric resource 112; providing safety measures during power transfer and changes of conditions in the power grid 114; logging activities; and providing self-contained control of power transfer and safety measures when communication with the flow control center 102 is interrupted. The remote IPF modules 134 will be described in greater detail below.

In another implementation, instead of having an IPF module 134, each electric resource 112 may have a corresponding transceiver (not shown) to communicate with a local charging component (not shown). The transceiver and charging component, in combination, may communicate with flow control center 102 to perform some or all of the above mentioned functions of IPF module 134. A transceiver and charging component are shown in FIG. 2B and are described in greater detail herein.

FIG. 2A shows another view of electrical and communicative connections to an electric resource 112. In this example, an electric vehicle 200 includes a battery bank 202 and a remote IPF module 134. The electric vehicle 200 may connect to a conventional wall receptacle (wall outlet) 204 of a residence 124, the wall receptacle 204 representing the peripheral edge of the power grid 114 connected via a residential powerline 206.

In one implementation, the power cord 208 between the electric vehicle 200 and the wall outlet 204 can be composed of only conventional wire and insulation for conducting alternating current (AC) power to and from the electric vehicle 200. In FIG. 2A, a location-specific connection locality module 210 performs the function of network access point—in this case, the Internet access point. A bridge 120 intervenes between the receptacle 204 and the network access point so that the power cord 208 can also carry network communications between the electric vehicle 200 and the receptacle 204. With such a bridge 120 and connection locality module 210 in place in a connection location, no other special wiring or physical medium is needed to communicate with the remote IPF module 134 of the electric vehicle 200 other than a conventional power cord 208 for providing residential line current at any conventional voltage. Upstream of the connection locality module 210, power and communication with the electric vehicle 200 are resolved into the powerline 206 and an Internet cable 104.

Alternatively, the power cord 208 may include safety features not found in conventional power and extension cords. For example, an electrical plug 212 of the power cord 208 may include electrical and/or mechanical safeguard components to prevent the remote IPF module 134 from electrifying or exposing the male conductors of the power cord 208 when the conductors are exposed to a human user.

In some embodiments, a radio frequency (RF) bridge (not shown) may assist the remote IPF module 134 in communicating with a foreign system, such as a utility smart meter (not shown) and/or a connection locality module 210. For example, the remote IPF module 134 may be equipped to communicate over power cord 208 or to engage in some form of RF communication, such as Zigbee or Bluetooth™, and the foreign system may be able to engage in a different form of RF communication. In such an implementation, the RF bridge may be equipped to communicate with both the foreign system and remote IPF module 134 and to translate communications from one to a form the other may understand, and to relay those messages. In various embodiments, the RF bridge may be integrated into the remote IPF module 134 or foreign system, or may be external to both. The communicative associations between the RF bridge and remote IPF module 134 and between the RF bridge and foreign system may be via wired or wireless communication.

FIG. 2B shows a further view of electrical and communicative connections to an electric resource 112. In this example, the electric vehicle 200 may include a transceiver 212 rather than a remote IPF module 134. The transceiver 212 may be communicatively coupled to a charging component 214 through a connection 216, and the charging component itself may be coupled to a conventional wall receptacle (wall outlet) 204 of a residence 124 and to electric vehicle 200 through a power cord 208. The other components shown in FIG. 2B may have the couplings and functions discussed with regard to FIG. 2A.

In various embodiments, transceiver 212 and charging component 214 may, in combination, perform the same functions as the remote IPF module 134. Transceiver 212 may interface with computer systems of electric vehicle 200 and communicate with charging component 214, providing charging component 214 with information about electric vehicle 200, such as its vehicle identifier, a location identifier, and a state of charge. In response, transceiver 212 may receive requests and commands which transceiver 212 may relay to vehicle 200's computer systems.

Charging component 214, being coupled to both electric vehicle 200 and wall outlet 204, may effectuate charge control of the electric vehicle 200. If the electric vehicle 200 is not capable of charge control management, charging component 214 may directly manage the charging of electric vehicle 200 by stopping and starting a flow of power between the electric vehicle 200 and a power grid 114 in response to commands received from a flow control server 106. If, on the other hand, the electric vehicle 200 is capable of charge control management, charging component 214 may effectuate charge control by sending commands to the electric vehicle 200 through the transceiver 212.

In some embodiments, the transceiver 212 may be physically coupled to the electric vehicle 200 through a data port, such as an OBD-II connector. In other embodiments, other couplings may be used. The connection 216 between transceiver 212 and charging component 214 may be a wireless signal, such as a radio frequency (RF), such as a Zigbee, or Bluetooth™ signal. And charging component 214 may include a receiver socket to couple with power cord 208 and a plug to couple with wall outlet 204. In one embodiment, charging component 214 may be coupled to connection locality module 210 in either a wired or wireless fashion. For example, charging component 214 might have a data interface for communicating wirelessly with both the transceiver 212 and locality module 210. In such an embodiment, the bridge 120 may not be required.

Further details about the transceiver 212 and charging component 214 are illustrated by FIG. 8B and described in greater detail herein.

FIG. 3 shows another implementation of the connection locality module 210 of FIG. 2, in greater detail. In FIG. 3, an electric resource 112 has an associated remote IPF module 134, including a bridge 120. The power cord 208 connects the electric resource 112 to the power grid 114 and also to the connection locality module 210 in order to communicate with the flow control server 106.

The connection locality module 210 includes another instance of a bridge 120, connected to a network access point 302, which may include such components as a router, switch, and/or modem, to establish a hardwired or wireless connection with, in this case, the Internet 104. In one implementation, the power cord 208 between the two bridges 120 and 120′ is replaced by a wireless Internet link, such as a wireless transceiver in the remote IPF module 134 and a wireless router in the connection locality module 210.

In other embodiments, a transceiver 212 and charging component 214 may be used instead of a remote IPF module 134. In such an embodiment, the charging component 214 may include or be coupled to a bridge 120, and the connection locality module 210 may also include a bridge 120′, as shown. In yet other embodiments, not shown, charging component 214 and connection locality module 210 may communicate in a wired or wireless fashion, as mentioned previously, without bridges 120 and 120′. The wired or wireless communication may utilize any sort of connection technology known in the art, such as Ethernet or RF communication, such as Zigbee, or Bluetooth.

System Layouts

FIG. 4 shows a layout 400 of the power aggregation system 100. The flow control center 102 can be connected to many different entities, e.g., via the Internet 104, for communicating and receiving information. The layout 400 includes electric resources 112, such as plug-in electric vehicles 200, physically connected to the grid within a single control area 402. The electric resources 112 become an energy resource for grid operators 404 to utilize.

The layout 400 also includes end users 406 classified into electric resource owners 408 and electrical connection location owners 410, who may or may not be one and the same. In fact, the stakeholders in a power aggregation system 100 include the system operator at the flow control center 102, the grid operator 404, the resource owner 408, and the owner of the location 410 at which the electric resource 112 is connected to the power grid 114.

Electrical connection location owners 410 can include:

Rental car lots—rental car companies often have a large portion of their fleet parked in the lot. They can purchase fleets of electric vehicles 200 and, participating in a power aggregation system 100, generate revenue from idle fleet vehicles.

Public parking lots—parking lot owners can participate in the power aggregation system 100 to generate revenue from parked electric vehicles 200. Vehicle owners can be offered free parking, or additional incentives, in exchange for providing power services.

Workplace parking—employers can participate in a power aggregation system 100 to generate revenue from parked employee electric vehicles 200. Employees can be offered incentives in exchange for providing power services.

Residences—a home garage can merely be equipped with a connection locality module 210 to enable the homeowner to participate in the power aggregation system 100 and generate revenue from a parked car. Also, the vehicle battery 202 and associated power electronics within the vehicle can provide local power backup power during times of peak load or power outages.

Residential neighborhoods—neighborhoods can participate in a power aggregation system 100 and be equipped with power-delivery devices (deployed, for example, by homeowner cooperative groups) that generate revenue from parked electric vehicles 200.

The grid operations 116 of FIG. 4 collectively include interactions with energy markets 412, the interactions of grid operators 404, and the interactions of automated grid controllers 118 that perform automatic physical control of the power grid 114.

The flow control center 102 may also be coupled with information sources 414 for input of weather reports, events, price feeds, etc. Other data sources 414 include the system stakeholders, public databases, and historical system data, which may be used to optimize system performance and to satisfy constraints on the power aggregation system 100.

Thus, a power aggregation system 100 may consist of components that:

communicate with the electric resources 112 to gather data and actuate charging/discharging of the electric resources 112;

gather real-time energy prices;

gather real-time resource statistics;

predict behavior of electric resources 112 (connectedness, location, state (such as battery State-Of-Charge) at a given time of interest, such as a time of connect/disconnect);

predict behavior of the power grid 114/load;

encrypt communications for privacy and data security;

actuate charging of electric vehicles 200 to optimize some figure(s) of merit;

offer guidelines or guarantees about load availability for various points in the future, etc.

These components can be running on a single computing resource (computer, etc.), or on a distributed set of resources (either physically co-located or not).

Power aggregation systems 100 in such a layout 400 can provide many benefits: for example, lower-cost ancillary services (i.e., power services), fine-grained (both temporal and spatial) control over resource scheduling, guaranteed reliability and service levels, increased service levels via intelligent resource scheduling, and/or firming of intermittent generation sources such as wind and solar power generation.

The power aggregation system 100 enables a grid operator 404 to control the aggregated electric resources 112 connected to the power grid 114. An electric resource 112 can act as a power source, load, or storage, and the resource 112 may exhibit combinations of these properties. Control of a set of electric resources 112 is the ability to actuate power consumption, generation, or energy storage from an aggregate of these electric resources 112.

FIG. 5 shows the role of multiple control areas 402 in the power aggregation system 100. Each electric resource 112 can be connected to the power aggregation system 100 within a specific electrical control area. A single instance of the flow control center 102 can administer electric resources 112 from multiple distinct control areas 501 (e.g., control areas 502, 504, and 506). In one implementation, this functionality is achieved by logically partitioning resources within the power aggregation system 100. For example, when the control areas 402 include an arbitrary number of control areas, control area “A” 502, control area “B” 504, . . . , control area “n” 506, then grid operations 116 can include corresponding control area operators 508, 510, . . . , and 512. Further division into a control hierarchy that includes control division groupings above and below the illustrated control areas 402 allows the power aggregation system 100 to scale to power grids 114 of different magnitudes and/or to varying numbers of electric resources 112 connected with a power grid 114.

FIG. 6 shows a layout 600 of a power aggregation system 100 that uses multiple centralized flow control centers 102 and 102′ and a directory server 602 for determining a flow control center. Each flow control center 102 and 102′ has its own respective end users 406 and 406′. Control areas 402 to be administered by each specific instance of a flow control center 102 can be assigned dynamically. For example, a first flow control center 102 may administer control area A 502 and control area B 504, while a second flow control center 102′ administers control area n 506. Likewise, corresponding control area operators (508, 510, and 512) are served by the same flow control center 102 that serves their respective different control areas.

In various embodiments, an electric resource may determine which flow control center 102/102′ administers its control area 502/504/506 by communicating with a directory server 602. The address of the directory server 602 may be known to electric resource 112 or its associated IPF module 134 or charging component 214. Upon plugging in, the electric resource 112 may communicate with the directory server 602, providing the directory server 112 with a resource identifier and/or a location identifier. Based on this information, the directory server 602 may respond, identifying which flow control center 102/102′ to use.

In another embodiment, directory server 602 may be integrated with a flow control server 106 of a flow control center 102/102′. In such an embodiment, the electric resource 112 may contact the server 106. In response, the server 106 may either interact with the electric resource 112 itself or forward the connection to another flow control center 102/102′ responsible for the location identifier provided by the electric resource 112.

In some embodiments, whether integrated with a flow control server 106 or not, directory server 602 may include a publicly accessible database for mapping locations to flow control centers 102/102′.

Flow Control Server

FIG. 7 shows a server 106 of the flow control center 102. The illustrated implementation in FIG. 7 is only one example configuration, for descriptive purposes. Many other arrangements of the illustrated components or even different components constituting a server 106 of the flow control center 102 are possible within the scope of the subject matter. Such a server 106 and flow control center 102 can be executed in hardware, software, or combinations of hardware, software, firmware, etc.

The flow control server 106 includes a connection manager 702 to communicate with electric resources 112, a prediction engine 704 that may include a learning engine 706 and a statistics engine 708, a constraint optimizer 710, and a grid interaction manager 712 to receive grid control signals 714. Grid control signals 714 are sometimes referred to as generation control signals, such as automated generation control (AGC) signals. The flow control server 106 may further include a database/information warehouse 716, a web server 718 to present a user interface to electric resource owners 408, grid operators 404, and electrical connection location owners 410; a contract manager 720 to negotiate contract terms with energy markets 412, and an information acquisition engine 414 to track weather, relevant news events, etc., and download information from public and private databases 722 for predicting behavior of large groups of the electric resources 112, monitoring energy prices, negotiating contracts, etc.

Remote IPF Module

FIG. 8A shows the remote IPF module 134 of FIGS. 1 and 2 in greater detail. The illustrated remote IPF module 134 is only one example configuration, for descriptive purposes. Many other arrangements of the illustrated components or even different components constituting a remote IPF module 134 are possible within the scope of the subject matter. Such a remote IPF module 134 has some hardware components and some components that can be executed in hardware, software, or combinations of hardware, software, firmware, etc. In other embodiments, executable instructions configured to perform some or all of the operations of remote IPF module 134 may be added to hardware of an electric resource 112 such as an electric vehicle that, when combined with the executable instructions, provides equivalent functionality to remote IPF module 134. References to remote IPF module 134 as used herein include such executable instructions.

The illustrated example of a remote IPF module 134 is represented by an implementation suited for an electric vehicle 200. Thus, some vehicle systems 800 are included as part of the remote IPF module 134 for the sake of description. However, in other implementations, the remote IPF module 134 may exclude some or all of the vehicles systems 800 from being counted as components of the remote IPF module 134.

The depicted vehicle systems 800 include a vehicle computer and data interface 802, an energy storage system, such as a battery bank 202, and an inverter/charger 804. Besides vehicle systems 800, the remote IPF module 134 also includes a communicative power flow controller 806. The communicative power flow controller 806 in turn includes some components that interface with AC power from the grid 114, such as a powerline communicator, for example an Ethernet-over-powerline bridge 120, and a current or current/voltage (power) sensor 808, such as a current sensing transformer.

The communicative power flow controller 806 also includes Ethernet and information processing components, such as a processor 810 or microcontroller and an associated Ethernet media access control (MAC) address 812; volatile random access memory 814, nonvolatile memory 816 or data storage, an interface such as an RS-232 interface 818 or a CANbus interface 820; an Ethernet physical layer interface 822, which enables wiring and signaling according to Ethernet standards for the physical layer through means of network access at the MAC/Data Link Layer and a common addressing format. The Ethernet physical layer interface 822 provides electrical, mechanical, and procedural interface to the transmission medium—i.e., in one implementation, using the Ethernet-over-powerline bridge 120. In a variation, wireless or other communication channels with the Internet 104 are used in place of the Ethernet-over-powerline bridge 120.

The communicative power flow controller 806 also includes a bidirectional power flow meter 824 that tracks power transfer to and from each electric resource 112, in this case the battery bank 202 of an electric vehicle 200.

The communicative power flow controller 806 operates either within, or connected to an electric vehicle 200 or other electric resource 112 to enable the aggregation of electric resources 112 introduced above (e.g., via a wired or wireless communication interface). These above-listed components may vary among different implementations of the communicative power flow controller 806, but implementations typically include:

-   -   an intra-vehicle communications mechanism that enables         communication with other vehicle components;     -   a mechanism to communicate with the flow control center 102;     -   a processing element;     -   a data storage element;     -   a power meter; and     -   optionally, a user interface.

Implementations of the communicative power flow controller 806 can enable functionality including:

-   -   executing pre-programmed or learned behaviors when the electric         resource 112 is offline (not connected to Internet 104, or         service is unavailable);     -   storing locally-cached behavior profiles for “roaming”         connectivity (what to do when charging on a foreign system,         i.e., when charging in the same utility territory on a foreign         meter or in a separate utility territory, or in disconnected         operation, i.e., when there is no network connectivity);     -   allowing the user to override current system behavior; and     -   metering power-flow information and caching meter data during         offline operation for later transaction.

Thus, the communicative power flow controller 806 includes a central processor 810, interfaces 818 and 820 for communication within the electric vehicle 200, a powerline communicator, such as an Ethernet-over-powerline bridge 120 for communication external to the electric vehicle 200, and a power flow meter 824 for measuring energy flow to and from the electric vehicle 200 via a connected AC powerline 208.

Power Flow Meter

Power is the rate of energy consumption per interval of time. Power indicates the quantity of energy transferred during a certain period of time, thus the units of power are quantities of energy per unit of time. The power flow meter 824 measures power for a given electric resource 112 across a bidirectional flow—e.g., power from grid 114 to electric vehicle 200 or from electric vehicle 200 to the grid 114. In one implementation, the remote IPF module 134 can locally cache readings from the power flow meter 824 to ensure accurate transactions with the central flow control server 106, even if the connection to the server is down temporarily, or if the server itself is unavailable.

Transceiver and Charging Component

FIG. 8B shows the transceiver 212 and charging component 214 of FIG. 2B in greater detail. The illustrated transceiver 212 and charging component 214 is only one example configuration, for descriptive purposes. Many other arrangements of the illustrated components or even different components constituting the transceiver 212 and charging component 214 are possible within the scope of the subject matter. Such a transceiver 212 and charging component 214 have some hardware components and some components that can be executed in hardware, software, or combinations of hardware, software, firmware, etc.

The illustrated example of the transceiver 212 and charging component 214 is represented by an implementation suited for an electric vehicle 200. Thus, some vehicle systems 800 are illustrated to provide context to the transceiver 212 and charging component 214 components.

The depicted vehicle systems 800 include a vehicle computer and data interface 802, an energy storage system, such as a battery bank 202, and an inverter/charger 804. In some embodiments, vehicle systems 800 may include a data port, such as an OBD-II port, that is capable of physically coupling with the transceiver 212. The transceiver 212 may then communicate with the vehicle computer and data interface 802 through the data port, receiving information from electric resource 112 comprised by vehicle systems 800 and, in some embodiments, providing commands to the vehicle computer and data interface 802. In one implementation, the vehicle computer and data interface 802 may be capable of charge control management. In such an embodiment, the vehicle computer and data interface 802 may perform some or all of the charging component 214 operations discussed below. In other embodiments, executable instructions configured to perform some or all of the operations of the vehicle computer and data interface 802 may be added to hardware of an electric resource 112 such as an electric vehicle that, when combined with the executable instructions, provides equivalent functionality to the vehicle computer and data interface 802. References to the vehicle computer and data interface 802 as used herein include such executable instructions.

In various embodiments, the transceiver 212 may have a physical form that is capable of coupling to a data port of vehicle systems 800. Such a transceiver 212 may also include a plurality of interfaces, such as an RS-232 interface 818 and/or a CANBus interface 820. In various embodiments, the RS-232 interface 818 or CANBus interface 820 may enable the transceiver 212 to communicate with the vehicle computer and data interface 802 through the data port. Also, the transceiver may be or comprise an additional interface (not shown) capable of engaging in wireless communication with a data interface 820 of the charging component 214. The wireless communication may be of any form known in the art, such as radio frequency (RF) communication (e.g., Zigbee, and/or Bluetooth™ communication). In other embodiments, the transceiver may comprise a separate conductor or may be configured to utilize a powerline 208 to communicate with charging component 214. In yet other embodiments, not shown, transceiver 212 may simply be a radio frequency identification (RFID) tag capable of storing minimal information about the electric resource 112, such as a resource identifier, and of being read by a corresponding RFID reader of charging component 214. In such other embodiments, the RFID tag might not couple with a data port or communicate with the vehicle computer and data interface 802.

As shown, the charging component 214 may be an intelligent plug device that is physically connected to a charging medium, such as a powerline 208 (the charging medium coupling the charging component 214 to the electric resource 112) and an outlet of a power grid (such as the wall outlet 204 shown in FIG. 2B). In other embodiments charging component 214 may be a charging station or some other external control. In some embodiments, the charging component 214 may be portable.

In various embodiments, the charging component 214 may include components that interface with AC power from the grid 114, such as a powerline communicator, for example an Ethernet-over-powerline bridge 120, and a current or current/voltage (power) sensor 808, such as a current sensing transformer.

In other embodiments, the charging component 214 may include a further Ethernet plug or wireless interface in place of bridge 120. In such an embodiment, data-over-powerline communication is not necessary, eliminating the need for a bridge 120. The Ethernet plug or wireless interface may communicate with a local access point, and through that access point to flow control server 106.

The charging component 214 may also include Ethernet and information processing components, such as a processor 810 or microcontroller and an associated Ethernet media access control (MAC) address 812; volatile random access memory 814, nonvolatile memory 816 or data storage, a data interface 826 for communicating with the transceiver 212, and an Ethernet physical layer interface 822, which enables wiring and signaling according to Ethernet standards for the physical layer through means of network access at the MAC/Data Link Layer and a common addressing format. The Ethernet physical layer interface 822 provides electrical, mechanical, and procedural interface to the transmission medium—i.e., in one implementation, using the Ethernet-over-powerline bridge 120. In a variation, wireless or other communication channels with the Internet 104 are used in place of the Ethernet-over-powerline bridge 120.

The charging component 214 may also include a bidirectional power flow meter 824 that tracks power transfer to and from each electric resource 112, in this case the battery bank 202 of an electric vehicle 200.

Further, in some embodiments, the charging component 214 may comprise an RFID reader to read the electric resource information from transceiver 212 when transceiver 212 is an RFID tag.

Also, in various embodiments, the charging component 214 may include a credit card reader to enable a user to identify the electric resource 112 by providing credit card information. In such an embodiment, a transceiver 212 may not be necessary.

Additionally, in one embodiment, the charging component 214 may include a user interface, such as one of the user interfaces described in greater detail below.

Implementations of the charging component 214 can enable functionality including:

-   -   executing pre-programmed or learned behaviors when the electric         resource 112 is offline (not connected to Internet 104, or         service is unavailable);     -   storing locally-cached behavior profiles for “roaming”         connectivity (what to do when charging on a foreign system or in         disconnected operation, i.e., when there is no network         connectivity);     -   allowing the user to override current system behavior; and     -   metering power-flow information and caching meter data during         offline operation for later transaction.

User Interfaces (UI)

Charging Station UI. An electrical charging station, whether free or for pay, can be installed with a user interface that presents useful information to the user. Specifically, by collecting information about the grid 114, the electric resource state, and the preferences of the user, the station can present information such as the current electricity price, the estimated recharge cost, the estimated time until recharge, the estimated payment for uploading power to the grid 114 (either total or per hour), etc. The information acquisition engine 414 communicates with the electric resource 112 and with public and/or private data networks 722 to acquire the data used in calculating this information.

The types of information gathered from the electric resource 112 could include an electric resource identifier (resource ID) and state information like the state of charge of the electric resource 112. The resource ID could be used to obtain knowledge of the electric resource type and capabilities, preferences, etc. through lookup with the flow control server 106.

In various embodiments, the charging station system including the UI might also gather grid-based information, such as current and future energy costs at the charging station.

User Charge Control UI Mechanisms. In various embodiments, by default, electric resources 112 may receive charge control management via power aggregation system 100. In some embodiments, an override control may be provided to override charge control management and charge as soon as possible. The override control may be provided, in various embodiments, as a user interface mechanism of the remote IPF module 134, the charging component 214, of the electric resource (for example, if electric resource is a vehicle 200, the user interface control may be integrated with dash controls of the vehicle 200) or even via a web page offered by flow control server 106. The control could be presented, for example, as a button, a touch screen option, a web page, or some other UI mechanism. In one embodiment, the UI may be the UI illustrated by FIG. 8C and discussed in greater detail below. In some embodiments, the override would be a one-time override, only applying to a single plug-in session. Upon disconnecting and reconnecting, the user may again need to interact with the UI mechanism to override the charge control management.

In some embodiments, the user may pay more to charge with the override on than under charge control management, thus providing an incentive for the user to accept charge control management. Such a cost differential may be displayed or rendered to the user in conjunction with or on the UI mechanism. This differential could take into account time-varying pricing, such as Time of Use (TOU), Critical Peak Pricing (CPP), and Real-Time Pricing (RTP) schemes, as discussed above, as well as any other incentives, discounts, or payments that might be forgone by not accepting charge control management.

UI Mechanism for Management Preferences. In various embodiments, a user interface mechanism of the remote IPF module 134, the charging component 214, of the electric resource (for example, if electric resource is a vehicle 200, the user interface control may be integrated with dash controls of the vehicle 200) or even via a web page offered by flow control server 106 may enable a user to enter and/or edit management preferences to affect charge control management of the user's electric resource 112. In some embodiments, the UI mechanism may allow the user to enter/edit general preferences, such as whether charge control management is enabled, whether vehicle-to-grid power flow is enabled or whether the electric resource 112 should only be charged with clean/green power. Also, in various embodiments, the UI mechanism may enable a user to prioritize relative desires for minimizing costs, maximizing payments (i.e., fewer charge periods for higher amounts), achieving a full state-of-charge for the electric resource 112, charging as rapidly as possible, and/or charging in as environmentally-friendly a way as possible. Additionally, the UI mechanism may enable a user to provide a default schedule for when the electric resource will be used (for example, if resource 112 is a vehicle 200, the schedule would be for when the vehicle 200 should be ready to drive). Further, the UI mechanism may enable the user to add or select special rules, such as a rule not to charge if a price threshold is exceeded or a rule to only use charge control management if it will earn the user at least a specified threshold of output. Charge control management may then be effectuated based on any part or all of these user entered preferences.

Simple User Interface. FIG. 8C illustrates a simple user interface (UI) which enables a user to control charging based on selecting among a limited number of high level preferences. For example, UI 2300 includes the categories “green”, “fast”, and “cheap” (with what is considered “green”, “fast”, and “cheap” varying from embodiment to embodiment). The categories shown in UI 2300 are selected only for the sake of illustration and may instead includes these and/or any other categories applicable to electric resource 112 charging known in the art. As shown, the UI 2300 may be very basic, using well known form controls such as radio buttons. In other embodiments, other graphic controls known in the art may be used. The general categories may be mapped to specific charging behaviors, such as those discussed above, by a flow control server 106.

Electric Resource Communication Protocol

FIG. 9 illustrates a resource communication protocol. As shown, a remote IPF module 134 or charging component 214 may be in communication with a flow control server 106 over the Internet 104 or another networking fabric or combination of networking fabrics. In various embodiments, a protocol specifying an order of messages and/or a format for messages may be used to govern the communications between the remote IPF module 134 or charging component 214 and flow control server 106.

In some embodiments, the protocol may include two channels, one for messages initiated by the remote IPF module 134 or charging component 214 and for replies to those messages from the flow control server 106, and another channel for messages initiated by the flow control server 106 and for replies to those messages from the remote IPF module 134 or charging component 214. The channels may be asynchronous with respect to each other (that is, initiation of messages on one channel may be entirely independent of initiation of messages on the other channel). However, each channel may itself be synchronous (that is, once a message is sent on a channel, another message may not be sent until a reply to the first message is received).

As shown, the remote IPF module 134 or charging component 214 may initiate communication 902 with the flow control server 106. In some embodiments, communication 902 may be initiated when, for example, an electric resource 112 first plugs in/connects to the power grid 114. In other embodiments, communication 902 may be initiated at another time or times. The initial message 902 governed by the protocol may require, for example, one or more of an electric resource identifier, such as a MAC address, a protocol version used, and/or a resource identifier type.

Upon receipt of the initial message by the flow control server 106, a connection may be established between the remote IPF module 134 or charging component 214 and flow control server 106. Upon establishing a connection, the remote IPF module 134 or charging component 214 may register with flow control server 106 through a subsequent communication 903. Communication 903 may include a location identifier scheme, a latitude, a longitude, a max power value that the remote IPF module 134 or charging component 214 can draw, a max power value that the remote IPF module 134 or charging component 214 can provide, a current power value, and/or a current state of charge.

After the initial message 902, the protocol may require or allow messages 904 from the flow control server 106 to the remote IPF module 134 or charging component 214 or messages 906 from remote IPF module 134 or charging component 214 to the flow control server 106. The messages 904 may include, for example, one or more of commands, messages, and/or updates. Such messages 904 may be provided at any time after the initial message 902. In one embodiment, messages 904 may include a command setting, a power level and/or a ping to determine whether the remote IPF module 134 or charging component 214 is still connected.

The messages 906 may include, for example, status updates to the information provided in the registration message 903. Such messages 906 may be provided at any time after the initial message 902. In one embodiment, the messages 906 may be provided on a pre-determined time interval basis. In various embodiments, messages 906 may even be sent when the remote IPF module 134 or charging component 214 is connected, but not registered. Such messages 906 may include data that is stored by flow control server 106 for later processing. Also, in some embodiments, messages 904 may be provided in response to a message 902 or 906.

Site Power Flow Manager

Modern electric vehicles benefit in a variety of ways from a centrally controlled smart charging program where a central server coordinates the charging activities of a number of vehicles. While many such smart charging programs may be operated by electric utilities to control electric vehicles over a wide area, many of the benefits of a smart charging program can be realized at a local level by the operator of a facility operating in isolation from the any other entity. In a place where multiple plug-in vehicles may park and connect to the grid, it is valuable to have site-level charging management.

As shown in FIG. 10, the charging process of electric vehicles 1000 is managed by a site power flow manager 1010 at the site-level 1020. Site-level charging management is an important feature at charging locations where multiple plug-in electric vehicles 1000 may park and connect to the grid 1030. Such locations/sites 1020 may include public or private parking lots, or the base of operations for a fleet.

There are a number of benefits for managing the power flow at the site-level. Having control over the flow of power is useful when, for example, the grid connection 1030 at the site 1020 is not capable of supporting every electric vehicle 1000, and/or other devices on site, that is simultaneously drawing power. In some instances, the wiring to specific charge points 1040 at the site, or to banks of charge points at the site 1020, may not be capable of supporting every vehicle 1000 drawing power at the same time. Many sites are subject to demand charges based on peak power draw during a time period (e.g. month), so avoiding power spikes can also save money. Furthermore, power usage can be tuned to the specific electric rate structure of the site.

A site power flow manager 1010 could address these issues, inter alia. Providing a power flow management system at the site-level allows important information to be taken as input, including but not limited to: electrical meter data for the site 1020 as a whole, and/or electrical meter data for specific charge points 1040 or banks of charge points. In addition, the system can consider information from devices, such as plug-in vehicles 1000, at the site that are connected to the electric grid 1030. Such information might be transmitted in a variety of ways, including by a power-line carrier or a wireless means. This information may include a unique identifier, resource type, current state of charge, and max power in/out levels. Further, the system can receive information about the electric rate structure of the site, and information about the electrical topology and power limitations of various circuits within the site. A connection to a power flow manager 1010 operates at a higher level of the grid topology, i.e. at the substation level or the control area level, so that the site power flow manager 1010 can receive information and also respond to requests, such as a demand response event, a reserves call, renewable resource following, or system regulation. In one embodiment, the site power flow manager 1010 and the higher level site controller can have priority rules, e.g. not overloading local circuits takes priority over remote requests.

A site power flow manager 1010 can analyze the current, and the predicted future, state of the world. In doing so, the site power flow manager 1010 can make various determinations, including whether or not to allow certain devices/vehicles 1000 to draw power. In addition, site power flow manager 1010 can request that the devices/vehicles 1000 provide power, and further control the power levels of the devices/vehicles 1000. These decisions could be made within constraints, such as not overloading a circuit or going over a certain total power draw. Such constraints may be performed, as in one embodiment, with prioritization, such as optimizing to get power to certain devices versus others. For example, the site power flow manager 1010 may charge vehicles 1000 that are at the lowest state of charge, that have been plugged in the longest, or that have priority for recharge. In an embodiment, the site power flow manager 1010 may allow for optimizing with regard to the overall site electric cost minimization or total cost minimization, or to recharge in the greenest, most efficient meaner.

Decisions made by the site power flow manager 1010 can be carried out in several ways, including controlling relays to open or close certain circuits. In addition, the site power flow manager 1010 can communicate with smart charging points 1040 or smart banks of charging points 1040 to control certain circuits or devices 1000 on those circuits. The site power flow manager 1010 may also communicate with the devices 1000 to give them a request or command for their power flow behavior, such as telling a vehicle 1000 to charge at half power or to recharge in an efficient manner. Such communications may traverse via a smart charging point 1040 or bank thereof. The site power flow manager 1010 may be located at the site 1020 being managed, but can also located remote to the site 1020.

FIG. 11 illustrates the site-level charging of electrical devices by a power flow manager 1110. The power flow manager receives site-level information 1120, and makes power flow decisions based on the site-level information 1130. In addition, power flow to the electrical devices is managed by the power flow manager 1140, such that the power flow manager responds to requests including demand response event, reserves call, renewable resource following, or system regulation.

Meta-Optimization Across Multiple Power Flow Management Strategies

Managing one or an aggregation of power resources (such as load, generation, storage, plug-in vehicles), power flow manager can use the combined capabilities of the assets under its control to implement a variety of beneficial services. These services may include regulation, spinning reserve, and/or peak avoidance. Regulation involves increasing or decreasing the load present on the grid in real time in order to maintain balance between power production and power consumption in the entire grid. Spinning reserve provides the ability to quickly make up a large amount of missing power after the failure of a generation or transmission asset within the grid. Peak avoidance results in reducing peak power consumption for the day, which is typically the most expensive power for the utility to provide.

There are many other similar services, such as to provide capacity or to provide renewable generation following. As the power flow manager may use any number of different strategies to decide how to dispatch the resources under management, it will be understood by those skilled in the art that other strategies, and combinations thereof, may be implemented in various embodiments. In one embodiment, the power flow manager may be a site power flow manager 1010, as shown in FIG. 10.

Such services provide a substantial cost savings to an electric utility. In many circumstances, it is also possible for a utility or other operator to sell these services through an energy market. While each of these services have very distinct characteristics from the perspective of the electric utility, the services are each implemented in fundamentally the same way on the power resource endpoint. That is, by selectively flowing power in to or out of the power resource in response to commands from the central power flow manager.

Because the same pool of resources can be used to implement each of the possible services, a conflict arises. As an example, If an entire population of electric vehicles is committed entirely to regulation services, that population not be able to fully participate in a peak avoidance program. Because the relative costs and benefits of the various services change over time, it is undesirable to simply pick the most valuable service and commit all the assets to it all of the time.

Given a set of such strategies, a meta-optimizer decides which strategy to use at appropriate times. The meta-optimizer may be located within the power flow manager. The meta-optimizer determines which resources are to be used in implementing a strategy. The determination may be based on a variety of factors, such as maximizing value generated and/or minimizing environmental impact. In an embodiment, the meta-optimizer chooses the strategy that is likely to generate the most value for a given time period, e.g. the next hour. The implementation may have a value function associated with each strategy, and then take the maximum value across all strategies.

The decision may vary by grid topological location. For example, if a given feeder is overloaded, the best decision for resources on that feeder may be to reduce the load, even if elsewhere on the grid a different strategy or action may be best.

The decision may also take into account multiple component requirements. For example, in managing plug-in vehicle recharging, it may be desirable to get vehicles recharged in a timely fashion, while also maximizing value created through other services provided.

In one embodiment, the decision may be based on predictions about the future. For example, it may be worth a certain amount at hour N to take some action, such as charging plug-in vehicles to provide down regulation. However, if that means the resources might be unavailable at hour N+1, when the resource may be worth more than at hour N, then the meta-optimizer might delay the action so that the resource is available to provide more value.

FIG. 12 shows an embodiment of a method for managing power flow by optimizing multiple power flow management strategies including coordinating charging activities 1210 and controlling power flow service 1220. A meta-optimizer can choose a power flow management strategy and an electrical device 1230 such that the power flow manager may implement the power flow management strategies 1240.

Avoiding Power Spikes During Energy Management Failures

Historically, utilities had to depend on the independent and random nature of electrical loads on the grid. While an individual electrical load is unpredictable and can be switched on or off at any time, each load is only a small part of total power consumption. The large number of individual loads on the electrical system provides a form of smoothing. Electrical consumption increases and decreases over time, but the overall change fluctuates along a somewhat predictable curve and power companies are able to adjust power production to match consumption.

In distributed energy management systems where communications are not 100% reliable, it is important that no loss of communications between the elements of the system or unexpected system controller failure cause unexpected system behavior. One particular behavior to be avoided is an unexpected, coordinated action across distributed resources that results from a failure mode. For example, when a controller suffers a failure, it could be detrimental to the electrical grid if all distributed resources started drawing power from the grid simultaneously.

The introduction of a smart charging or energy management system causes otherwise isolated loads to potentially operate in concert. This creates the possibility of adverse coordinated action in the event of system failure. In particular, if each electrical load is designed to revert to a maximum energy consumption level in the case of communications loss, then a failure of the management system may result in an instantaneous and coordinated spike in electricity demand. When the population of controlled devices is sufficiently large, the spike in demand can exceed the utility's capacity for rapid adjustment and result in a blackout.

An example of a failure mode includes failed communications between individual resources and the master controller or controllers. Communications can also fail between a controller and some or all of the resources. In addition, a controller or a set of controllers can fail in a non-network related way that renders such controllers incapable of communicating with the resources. A failure mode may also be a design defect shared by a large population of resources causing the population to simultaneously lose communications capabilities when an unexpected event occurred.

In the case of any failure mode, the system behavior should be predictable and non-disruptive. To prevent disruptive impacts on the grid as a whole, endpoints normally controlled by a central energy management server may employ a variety of safe failure modes. A system for maintaining predictable behavior may include a distributed resource with various capabilities, including the ability to receive/enact a sequence of commands to be executed at one or various points in time.

An example of a safe failure mode includes maintaining stable (non-changing) behavior for a defined period of time around a failure event. For example, after communications is lost, an isolated EVSE can continue charging at the rate last specified by the charge management controller. After some period of time, the EVSE may slowly transition to a different autonomous strategy.

Another safe failure mode includes executing a pre-arranged behavior in the event of a failure condition. As an example, if a group of EVSE's was connected to a electrical circuit that was only capable of providing 70% of the combined maximum power draw of the group, each EVSE could be pre-programmed to operate at 70% of capacity in the event of communications failure.

Yet another safe failure mode includes executing state transitions in pre-arranged behaviors at the determined time offset by a random interval of time. As an example, EVSE's that are off when communications fail could wait a random amount of time between 0 and 30 minutes before powering on. This random startup causes the increase in power consumption to be spread over time, allowing the utility the opportunity to respond.

A safe failure mode may also include using predictions about resource behaviors, such as the comings and goings from the system, to further enhance the estimate of the state of the world. As an example, if an EVSE is normally commanded to consume power along a curve (to harmonize with grid conditions), the EVSE could be programmed to follow type-based typical curve in the absence of communications. Since the central smart charging system would know the curve the detached EVSE was following, its behavior could still be input in to the charge management algorithms.

FIG. 13 illustrates an embodiment for managing power flow using safe failure modes including coordinating charging activities of electrical devices 1310 and detecting a system failure event 1320. The power flow manager implements a safe failure mode 1330 that provides predictable and non-disruptive system behavior.

Generation-Stack-Aware Dispatch of Resources

One potential goal of a distributed energy management system is to dispatch resources to minimize cost. A basic cost reduction strategy is to reduce electricity consumption when electricity prices are high. This basic strategy reduces the cost of electricity consumed by the endpoints under active management.

A more advanced strategy could manipulate the electricity consumed by controlled endpoints in a way that impacts the market price of power. Such a system can reduce the cost of providing power to all devices within a utility's service area, not just those under active management.

In many regions, power production is managed by separate entities from the utilities responsible for distribution. Utilities purchase electricity from Power producers, and re-sell it to their customers.

Often, the transactions between power producers and distribution utilities take place in formalized market. Such a market typically operates as a single price auction. In such a market, each power producer states the price at which they are willing to provide power, and power production is allocated to the cheapest producers first, moving up the stack to more expensive produces until sufficient power has been obtained. The last (highest) price selected set the price that all power producers are paid.

Each type of generation asset in an energy generation system, such as the electrical grid, has a marginal cost. Generation assets are dispatched in the order of increasing marginal cost. The most expensive generator dispatched at any time sets the cost basis for energy generation.

Different types of power plants have sharply different marginal costs of operation. For example, Hydroelectric is often much cheaper than gas turbines. As a result, there may be a sharp increase in the cost of electricity as available hydro is exhausted, and the gas turbines begin coming online.

At times, a distributed energy manager can remove enough load from the system to eliminate the need for higher cost generation, thereby decreasing the total cost to provide service.

The distributed energy manager can minimize the total daily cost to provide energy generation by forecasting total system and dispatchable load. The distributed energy manager schedules dispatchable load to draw power from the grid at times that will minimize cost based on the available generation stack. Altering the total price of power paid has a larger financial impact than the amount paid specifically for automotive power. Also, moving the market may be easier at one time of day than another. As a result, dispatchable load will not always be scheduled to the lowest-cost time of day, but rather when it will have the most beneficial overall effect to the utility.

Further, the generation stack can change from region to region, and load profiles and consumption can change daily. Therefore, the present method will produce different dispatch patterns in different regions.

FIG. 14 shows an embodiment of managing power flow using generation stacks of power production to reduce cost of providing power to electrical devices. Charge activities are coordinated by a power flow manager 1410. A power production stack is controlled the power flow manager 1420 such that the power production stack orders available power. Based on a cost reduction strategy, a dispatchable load is removed 1430. The dispatchable load is listed in the power production stack.

Business Model of Selling Aggregated Power Resource Management Services to Power Generators or Others

Power resource management services include aggregating the following: plug-in vehicles, thermostats, residential or commercial/industrial load, or fixed energy storage. Such services provide regulation, reserves, load shifting, renewable resource following, or peak avoidance. A power flow manager is able to provide a variety of services that can improve the stability of the electric grid. For example, electricity consumption of distributed resources can be increased and decreased as necessary to absorb the differences between electricity production and consumption on the grid.

Customers for aggregated power resource management services include electric utilities, ISOs, and TSOs. Such entities are primarily responsible for the stability of the grid. But aggregated power resource management services may be sold to various types of power generators.

Some classes of electricity generation suffer from a high degree of intermittency, meaning that their power production is irregular. By bundling this irregular power production with the smoothing/stabilizing abilities of aggregated power resource management assets, it is possible to produce a higher grade of wholesale power, which may be more easily sold in energy markets.

In one example, a wind farm is the buyer of aggregated power resource management services. Wind farms are susceptible to fluctuations in the supply and demand of energy. For example, prices for energy may drop drastically when the amount of wind is great, or unexpectedly high. In addition, wind farms may be temporarily disconnected from a grid when there is not enough transmission or other capacity to absorb the power.

Economical issues resulting from such instability in the supply or demand of energy can be effectively addressed by providing owners of intermittent renewable generation with aggregated power resource management services. Power generators may increase their net load from the aggregated power resources when there is a large and/or unexpectedly high amount of wind, and decrease net load with there is a small and/or unexpectedly low amount of wind.

In an embodiment, power generators can use aggregated power resource management to smooth sudden ramping events in power output, or to firm the power output to a desired level. The sum of power generation plus net load from the aggregated power resources can be made constant, or less susceptible to changes in the supply or demand of energy.

As a result, power generators such as power plants may retain the value of the energy they create. Such an integration allow the operator of the generation asset to take direct action to address the intermittency issues associated with their type of generation. In some markets, this may be far more desirable than waiting for other parties to provide such services through the marketplace.

CONCLUSION

Although systems and methods have been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described. Rather, the specific features and acts are disclosed as examples of implementations of the claimed methods, devices, systems, etc. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention. 

1. A method for managing power flow at a local site, comprising the steps: site-level charging of a plurality of electrical devices by a power flow manager, wherein the power flow manager runs a smart charging program, wherein the power flow manager coordinates charging activities of the plurality of electrical devices, wherein the plurality of electrical devices are located at the local site; receiving site-level information, wherein the site-level information is received by the power flow manager; making power flow decisions based on the site-level information, wherein the power flow decisions are made by the power flow manager; and, managing power flow to the plurality of electrical devices by the power flow manager, wherein the power flow manager responds to requests.
 2. The method of claim 1, wherein the power flow manager is a central server.
 3. The method of claim 1, wherein the power flow manager is located at the local site.
 4. The method of claim 1, wherein the power flow manager is located remotely from the local site.
 5. The method of claim 1, wherein the electrical devices are electric vehicles.
 6. The method of claim 1, wherein the site-level information is selected from a group consisting of the following: electrical meter data for the local site, electrical meter data for at least one charge point; information from at least one of the plurality of electrical devices; electric rate information for the local site; electrical topology information; power limitation information; or priority rules.
 7. The method of claim 1, wherein the requests are selected from the group consisting of the following: demand response event, reserves call, renewable resource following, or system regulation.
 8. The method of claim 1, wherein the power flow manager communicates with at least one of the plurality of electrical.
 9. The method of claim 1, wherein the power flow manager communicates with at least one charge point.
 10. The method of claim 1, wherein the power flow decisions are selected from the group consisting of the following: to provide power, to draw power, to control power levels.
 11. The method of claim 1, wherein the power flow decisions are made based on constraints, priorities, optimizations, or efficiencies.
 12. The method of claim 1, wherein the power flow decisions are implemented by an action selected from the group consisting of the following: controlling relays to open close circuits; communicating to charging points to control circuits or devices on the circuits; communicating to at least one of the plurality of devices to provide a command for power flow behavior.
 13. A system for managing power flow at a local site, comprising: a power flow manager, wherein the power flow manager coordinates charging activities of a plurality of electrical devices, wherein the plurality of electrical devices are located at the local site; a plurality of charge points connected to the power flow manger, wherein the plurality of charge points are operable to connect to the plurality of electrical devices, wherein the plurality of charge points are located at the local site; site-level information, wherein the site-level information is received by the power flow manager; and, power flow decisions based on the site-level information, wherein the power flow decisions are made by the power flow manager.
 14. The system of claim 13, wherein the power flow manager is a central server.
 15. The system of claim 13, wherein the power flow manager is located at the local site.
 16. The system of claim 13, wherein the power flow manager is located remotely from the local site.
 17. The system of claim 13, wherein the electrical devices are electric vehicles.
 18. The system of claim 13, wherein the site-level information is selected from a group consisting of the following: electrical meter data for the local site, electrical meter data for at least one charge point; information from at least one of the plurality of electrical devices; electric rate information for the local site; electrical topology information; power limitation information; or priority rules.
 19. The system of claim 13, wherein the power flow manager communicates with at least one charge point.
 20. The system of claim 13, wherein the power flow manager communicates with at least one of the plurality of electrical.
 21. The system of claim 20, wherein the power flow manager communicates with at least one of the plurality of electrical via at least one charge point.
 22. The system of claim 20, wherein the power flow manager communicates with at least one of the plurality of electrical via a wireless connection.
 23. A system for managing power flow for optimization of multiple power flow management strategies, comprising: a power flow manager, wherein the power flow manager coordinates charging activities of a plurality of electrical devices; power flow services, wherein the power flow services are controlled by the power flow manager; power flow management strategies, wherein the power flow management strategies are implemented by the power flow manager; and, a meta-optimizer, wherein the meta-optimizer chooses at least one of the power flow management strategies, wherein the meta-optimizer chooses at least one of the electrical devices to utilize for implementing the at least one of the power flow management strategies.
 24. The system of claim of 23, wherein the power flow services are selected from a group consisting of the following: regulation, spinning reserve, peak avoidance, or renewable generation following.
 25. The system of claim of 23, wherein the meta-optimizer choices are based on maximizing value generated.
 26. The system of claim of 23, wherein the meta-optimizer choices are based on minimizing environmental impact.
 27. The system of claim of 23, wherein the meta-optimizer choices are based on a value function associated with the at least one of the power flow management strategies.
 28. The system of claim of 23, wherein the meta-optimizer choices are based on a grid topological location.
 29. The system of claim of 23, wherein the meta-optimizer choices are based on multiple component requirements.
 30. The system of claim of 23, wherein the meta-optimizer choices are based on predictions.
 31. The system of claim of 23, wherein the electrical devices are electric vehicles.
 32. A method for managing power flow by optimizing multiple power flow management strategies, comprising: coordinating charging activities of a plurality of electrical devices, wherein the charge activities are coordinated by a power flow manager; controlling power flow services, wherein the power flow services are controlled by the power flow manager; choosing at least one of the power flow management strategies, wherein the at least one of the power flow management strategies is chosen by a meta-optimizer; choosing at least one of the electrical devices to utilize for implementing the at least one of the power flow management strategies, wherein the at least one of the electrical devices is chosen by the meta-optimizer; and, implementing power flow management strategies, wherein the power flow management strategies are implemented by the power flow manager.
 33. The method of claim of 32, wherein the power flow services are selected from a group consisting of the following: regulation, spinning reserve, peak avoidance, or renewable generation following.
 34. The method of claim of 32, wherein the meta-optimizer choices are based on factors selected from a group consisting of the following: maximizing value generated; minimizing environmental impact; a value function associated with the at least one of the power flow management strategies; a grid topological location; multiple component requirements; or predictions.
 35. The method of claim of 32, wherein the meta-optimizer is the power flow manager.
 36. The method of claim of 32, wherein the power flow manager is a site power flow manager that managing power flow at a local site.
 37. The method of claim of 32, wherein the electrical devices are electric vehicles.
 38. A system for managing power flow using safe failure modes, comprising: a power flow manager, wherein the power flow manager coordinates charging activities of a plurality of electrical devices; a system failure event; and, a safe failure mode, wherein the safe failure mode is implemented by the power flow manager, wherein the safe failure mode provides that the charging activities be coordinated in a predictable and non-disruptive manner.
 39. The system of claim of 38, wherein the system failure event is generated as a result of an introduction of a smart charging or energy management system.
 40. The system of claim of 38, wherein the system failure event results in a spike in electricity demand.
 41. The system of claim of 38, wherein the system failure event occurs as a result of a failure in communications between the plurality of electrical devices and a master controller.
 42. The system of claim of 38, wherein the system failure event occurs as a result of a failure in a controller, wherein the controller is incapable of communicating with the plurality of electrical devices.
 43. The system of claim of 38, wherein the system failure event occurs as a result of a design defect shared by the plurality of electrical devices causing the plurality of electrical devices to simultaneously lose communications capabilities.
 44. The system of claim of 38, wherein the safe failure mode comprises maintaining a stable non-changing behavior for a defined period of time around a failure event.
 45. The system of claim of 38, wherein the safe failure mode comprises executing a prearranged behavior in the event of a failure condition.
 46. The system of claim of 38, wherein the safe failure mode comprises executing state transitions in prearranged behaviors at a determined time offset by a random interval of time.
 47. The system of claim of 38, wherein the safe failure mode comprises using predictions about resource behaviors.
 48. The system of claim of 38, wherein the electrical devices are electric vehicles.
 49. A method for managing power flow using safe failure modes, comprising: coordinating charging activities of a plurality of electrical devices, wherein the charge activities are coordinated by a power flow manager; detecting a system failure event, wherein the system failure event is detected by a power flow manager; and, implementing a safe failure mode, wherein the safe failure mode is implemented by the power flow manager, wherein the safe failure mode provides that the charging activities be coordinated in a predictable and non-disruptive manner.
 50. The method of claim of 49, wherein the system failure event is generated as a result of an introduction of a smart charging or energy management system.
 51. The method of claim of 49, wherein the system failure event results in a spike in electricity demand.
 52. The method of claim of 49, wherein the system failure event occurs as a result of a failure in communications between the plurality of electrical devices and a master controller.
 53. The method of claim of 49, wherein the system failure event occurs as a result of a failure in a controller, wherein the controller is incapable of communicating with the plurality of electrical devices.
 54. The method of claim of 49, wherein the system failure event occurs as a result of a design defect shared by the plurality of electrical devices causing the plurality of electrical devices to simultaneously lose communications capabilities.
 55. The method of claim of 49, wherein the safe failure mode comprises maintaining a stable non-changing behavior for a defined period of time around a failure event.
 56. The method of claim of 49, wherein the safe failure mode comprises executing a prearranged behavior in the event of a failure condition.
 57. The method of claim of 49, wherein the safe failure mode comprises executing state transitions in prearranged behaviors at a determined time offset by a random interval of time.
 58. The method of claim of 49, wherein the safe failure mode comprises using predictions about resource behaviors.
 59. The method of claim 49, wherein the electrical devices are electric vehicles.
 60. A system for managing power flow using generation stacks of power production to reduce cost of providing power to electrical devices, comprising: a power flow manager, wherein the power flow manager coordinates charging activities of a plurality of electrical devices; a power production stack, wherein the power flow manager controls the power production stack, wherein the power production stack orders available power; and, a dispatchable load, wherein the dispatchable load is listed in the power production stack, wherein the dispatchable load is removed based on a cost reduction strategy.
 61. The system of claim 60, wherein the available power is ordered based on power prices ordered from cheapest to most expensive.
 62. The system of claim 60, wherein the dispatchable load is the most expensive load listed in the power production stack.
 63. The system of claim 60, wherein the available power is provided by a plurality of power producers.
 64. The system of claim 60, wherein the cost reduction strategy is to decrease a cost of providing power services to the plurality of electrical devices.
 65. The system of claim 60, wherein the cost reduction strategy is to decrease a cost of providing power services to the plurality of electrical devices, wherein the cost is a daily cost.
 66. The system of claim 60, wherein the cost reduction strategy is to minimize a cost based on the power production stack.
 67. The system of claim 60, wherein the cost reduction strategy is to dispatch the most expensive load.
 68. The system of claim 60, wherein the cost reduction strategy is based on a region.
 69. The system of claim 60, wherein the cost reduction strategy comprises forecasting the dispatchable load.
 70. The system of claim 60, wherein the electrical devices are electric vehicles.
 71. A method for managing power flow using generation stacks of power production to reduce cost of providing power to electrical devices, comprising: coordinating charging activities of a plurality of electrical devices, wherein the charge activities are coordinated by a power flow manager; controlling a power production stack, wherein the power flow manager controls the power production stack, wherein the power production stack orders available power; removing a dispatchable load, wherein the dispatchable load is listed in the power production stack, wherein the dispatchable load is removed based on a cost reduction strategy.
 72. The system of claim 71, wherein the available power is ordered based on power prices ordered from cheapest to most expensive.
 73. The system of claim 71, wherein the dispatchable load is the most expensive load listed in the power production stack.
 74. The system of claim 71, wherein the available power is provided by a plurality of power producers.
 75. The system of claim 71, wherein the cost reduction strategy is to decrease a cost of providing power services to the plurality of electrical devices.
 76. The system of claim 71, wherein the cost reduction strategy is to decrease a cost of providing power services to the plurality of electrical devices, wherein the cost is a daily cost.
 77. The system of claim 71, wherein the cost reduction strategy is to minimize a cost based on the power production stack.
 78. The system of claim 71, wherein the cost reduction strategy is to dispatch the most expensive load.
 79. The system of claim 71, wherein the cost reduction strategy is based on a region.
 80. The system of claim 71, wherein the cost reduction strategy comprises forecasting the dispatchable load.
 81. The system of claim 71, wherein the electrical devices are electric vehicles.
 82. The method of claim 71, wherein the electrical devices are electric vehicles. 